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The software annotates text with 41 broad semantic categories (Wordnet supersenses) for both nouns and verbs; i.e., it performs both sense disambiguation and named-entity recognition. The tagger implements a discriminatively-trained Hidden Markov Model.
The aim of this project is to highlight the effect of lexical chain scoring metrics and keyword extraction techniques on summary generation. We present our own chain-based keyword extraction system using WordNet lexical database.